The whole dataset (df) have 1905740 observations and 82 columns. There are no repeated rows (each row have something different like different id value of exercise execution or id of implement used in an exercise). In this version of dataset, each row tells about different exercise execution (when id of exercise execution is repeated, it means that there are multiple different ids of implements given for one exercise execution).
The dataset can be subset when it comes to id_session_execution and there is only dataset with session executions (only one row for each session execution) - df_session_exe. It can be also subset by each user (there is only one row for each user) - df_users_only.
For whole dataset, there are columns:
Here, most of the columns have duplicated values because for user could do multiple exercise executions and multiple sessions. It is similar with the id_session_execution - in one executed session there are multiple exercises executed - so the id values will be duplicated.
For dataset only with one unique value for each user (df_users_only), only valuable variables are id_users, created_at_users, updated_at_users, gender, date_of_birth, height, weight, activity_level, goal, body_type, body_fat, newsletter_subscription, notifications_setting, training_days_setting, language, points, scientific_data_usage, best_weekly_streak_users, BMI, BMI_category, total_sessions_users2, total_time_users2, total_reps_users2, reps_per_session_users2, total_calories_users2, kcal_per_session_users2, but not all them will be relevant for the analysis.
This data frame has 3172 users and 26 columns that describe those users.
For dataset with only one unique value for each id_session_execution (df_session_exe) the valuable variables may be id_session_execution, difficulty_feedback_session_execution, enjoyment_feedback_session_execution, reps_executed_session_execution, updated_at_session_execution, discarded_session_execution, id_sessions, order_sessions, time_duration_sessions, code_name_sessions, name_en_sessions, id_user_programs, created_at_user_programs, updated_at_user_programs, active_user_programs, current_session_id_user_programs, completed_user_programs, id_programs, created_at_programs, updated_at_programs, pro_programs, available_programs, strength_programs, endurance_programs, technique_programs, flexibility_programs, intensity_programs, name_en_programs, description_en_programs, total_time_session_execution, total_reps_session_execution, total_time_session_execution_min, reps_per_min_session_execution, exercise_execution_time_min, calories_session_execution, Year/Week_session_exe, Period_session_exe.
This data frame has 49428 sessions executed (rows).
The variables that will have descriptive statistics for all rows:
| count | mean | std | min | 25% | 50% | 75% | max | var | skewness | kurtosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| reps_executed_ex_ex | 1905740.00 | 6.67 | 8.79 | 0.00 | 0.00 | 5.00 | 10.00 | 271.00 | 77.29 | 4.78 | 53.70 |
| execution_time_ex_ex | 1905740.00 | 35.12 | 27.32 | 0.00 | 16.00 | 30.00 | 46.00 | 200.00 | 746.17 | 1.75 | 5.25 |
| met_multiplier_exercises | 1905740.00 | 2.87 | 2.26 | 1.00 | 1.00 | 3.00 | 3.80 | 23.00 | 5.10 | 5.81 | 49.03 |
| calories | 1905740.00 | 2.15 | 2.26 | 0.00 | 0.73 | 1.50 | 2.90 | 101.22 | 5.13 | 2.88 | 22.32 |
Reps_executed_ex_ex have mean 6.67 (SD 8.79), that means, users that were executing exercises in average of 6 times per exercise. Maximum value of reps in executed exercise is 271. Median is 5 (IQR 0 - 10) reps in an exercise. It would be sensible to check those values again, but after excluding all of the zeros and exercises called rest. Mean value of execution_time_ex_ex is 35 seconds per exercise (SD 27). Median is 30 seconds (IQR 16 - 46) and maximum is 200 seconds in an exercise. Again, it would be sensible to check the data, but not including exercises with rest name. When treating met_multiplier_exercises as numeric value, then mean value of met of all exercises done is 2.87 (SD 2.26), which is Light-Intensity Activity. Median is 3 (IQR 1 - 3.8), which is Moderate-Intensity Activity and maximum is 23, which is High-Intensity Activity. Mean value of burned calories in an executed exercise is 2.15 (SD 2.26), median is 1.5 (IQR 0.73 - 2.9) and the maximum 101.22 burned calories in one exercise. In all of those variables it would be sensible to exclude exercises with name *rest*.
| count | mean | std | min | 25% | 50% | 75% | max | var | skewness | kurtosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| reps_executed_ex_ex | 1334750.00 | 9.51 | 9.10 | 0.00 | 5.00 | 8.00 | 10.00 | 271.00 | 82.74 | 5.32 | 60.03 |
| execution_time_ex_ex | 1334750.00 | 38.27 | 27.97 | 0.00 | 21.00 | 31.00 | 50.00 | 200.00 | 782.14 | 1.82 | 5.09 |
| met_multiplier_exercises | 1334750.00 | 3.66 | 2.27 | 1.00 | 2.80 | 3.50 | 3.80 | 23.00 | 5.16 | 7.30 | 58.47 |
| calories | 1334750.00 | 2.83 | 2.39 | 0.00 | 1.34 | 2.20 | 3.59 | 101.22 | 5.69 | 2.80 | 22.57 |
Reps_executed_ex_ex have increased mean - from 6.67 (SD 8.79) to 9.51 (SD 9.1), that means, users that were executing exercises in average of almost 10 times per exercise. Maximum value of reps in executed exercise has the same level as before - 271. Median increased from 5 (IQR 0 - 10) to 8 (IQR 5 - 10) reps in an exercise.
Mean value of execution_time_ex_ex increased from 35 seconds per exercise (SD 27) to 38 seconds per exercise (SD 28). Median increased from 30 seconds (IQR 16 - 46) to 31 seconds (IQR 21 - 50) and maximum is still 200 seconds in an exercise.
In met_multiplier_exercises mean value of met of all exercises done increased from 2.87 (SD 2.26) to 3.66 (SD 2.27), which is Moderate-Intensity Activity. Median increased from 3 (IQR 1 - 3.8) to 3.5 (IQR 2.8 - 3.8), which is still Moderate-Intensity Activity and maximum stayed at 23, which is High-Intensity Activity.
Mean value of burned calories in an executed exercise increased from 2.15 (SD 2.26) to 2.83 (SD 2.39), median increased from 1.5 (IQR 0.73 - 2.9) to 2.2 (1.34 - 3.59) and the maximum stayed at 101.22 burned calories in one exercise.
It is possible to check from which distribution data can come from (or is the closest to). Here will be used distfit function from distfit package. Every variable will be checked separately. The criterion of determination for best fit is RSS (residual sum of squares). The RSS describes the deviation predicted from actual empirical values of data. A small RSS indicates a tight fit of the model to the data. RSS is computed by
$$ RSS = \sum_{i=1}^{n} \left(y - f(x_i)\right)^2 $$where $y_i$ is the i-th value of the variable to be predicted, $x_i$ is the i-th value of the explanatory variable, and $f(x_i)$ is the predicted value of $y_i$ (also termed as $\hat{y_i}$). (Source: https://erdogant.github.io/distfit/pages/html/Parametric.html) In the analysis will be shown the best fit for each variable and its plot.
[distfit] >fit.. [distfit] >transform.. [distfit] >[expon] [0.00 sec] [RSS: 0.000254757] [loc=0.000 scale=6.672] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nexpon\nRSS(loc=0, scale=6.67241)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[genextreme] [43.6 sec] [RSS: 0.000679649] [loc=22.362 scale=18.326] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngenextreme\nRSS(c=-0.110198, loc=22.3622, scale=18.3258)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[expon] [0.00 sec] [RSS: 0.407001] [loc=1.000 scale=1.866] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nexpon\nRSS(loc=1, scale=1.86605)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[expon] [0.00 sec] [RSS: 0.000258582] [loc=0.000 scale=2.154] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nexpon\nRSS(loc=0, scale=2.15362)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[genextreme] [26.3 sec] [RSS: 0.000534944] [loc=5.773 scale=4.849] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngenextreme\nRSS(c=-0.159959, loc=5.77318, scale=4.84937)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[genextreme] [27.9 sec] [RSS: 0.000448682] [loc=25.467 scale=18.373] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngenextreme\nRSS(c=-0.108197, loc=25.467, scale=18.3734)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[t] [5.77 sec] [RSS: 0.0698539] [loc=3.388 scale=0.554] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nt\nRSS(df=2.43823, loc=3.38815, scale=0.554243)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[beta] [23.9 sec] [RSS: 0.000551249] [loc=-0.141 scale=14778917904.728] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nbeta\nRSS(a=1.80182, b=8.96173e+09, loc=-0.14053, scale=1.47789e+10)'}, xlabel='Values', ylabel='Frequency'>)
The data don't follow normal distribution.
It is possible to take met_multiplier_exercises as a categorical variable, so it will be done as it.
| Total | 1.0 | 3.5 | 3.8 | 2.5 | 3.0 | 3.2 | 4.0 | 2.3 | 2.8 | 5.0 | 4.2 | 2.6 | 5.2 | 3.9 | 3.6 | 23.0 | 5.5 | 12.0 | 2.9 | 4.5 | 8.0 | 2.0 | 6.0 | 4.8 | 4.3 | 5.3 | 7.0 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 1905740 | 571358 | 278906 | 205123 | 150585 | 116442 | 97140 | 85732 | 78730 | 76550 | 60891 | 54420 | 36266 | 19414 | 19012 | 17007 | 15455 | 4743 | 4444 | 3528 | 3123 | 2695 | 1982 | 909 | 890 | 213 | 160 | 22 |
| Percent | 100.0% | 29.98% | 14.64% | 10.76% | 7.9% | 6.11% | 5.1% | 4.5% | 4.13% | 4.02% | 3.2% | 2.86% | 1.9% | 1.02% | 1.0% | 0.89% | 0.81% | 0.25% | 0.23% | 0.19% | 0.16% | 0.14% | 0.1% | 0.05% | 0.05% | 0.01% | 0.01% | 0.0% |
Most of the exercises done have met_multiplier equal to 1 (30%).
| Total | Rest | Knee push-up | Pull-up | Squat | Paleo sit-up | Burpee | Push-up | Dips | Skipping | Bridge | Lunges (right) | Lunges (left) | Jumping squat | Free thruster | Sprint | Side lunge | Chin up | Plank pivot | Wall climb | Leg raises | Superman | Leg lifts | Jumping jacks | Plank balance | Side to side squat | Mckenzie | Plank | Glute march | Diamond push-up | Plank spider | Semi burpee | Sit-up | Windshield wiper | Flow a | Mountain runner | Hindu push-up | Bulgarian squat (left) | Bulgarian squat (right) | Diver | Suspended row | Backward lunge | Pallof press (left) | Handstand push-up | Isometric bridge | Mountain climber | Pallof press (right) | V sit-up | Swings | 1 leg bridge (left) | 1 leg bridge (right) | Horizontal jump | Mountain climbers up | Forward lunge | Semi V sit-up | Jumping lunge | Donkey kicks | Rocket (right) | Mountain climbers down | Rocket (left) | Plank taps (shoulder, hip, knee, ankle) | Shoulder swimmers | Side plank (right) | Push-up with hand lift | 1 leg dead lift (right) | 1 leg dead lift (left) | Forward thrust | Deck squat | Flow b | Russian twist | Press (right) | Side plank (left) | Press (left) | Australian pull-up | Weighted backward lunge | Double jump rope | Row (left) | Assisted pistol squat with box (right) | Row (right) | Burrol | Goblet squat | Assisted pistol squat with box (left) | Reptile push-up | 2 legs half burpee | Spider push-up | Star jump | Clean (left) | Clean (right) | Plank extension | Ring dips 1 | Weighted side lunge | Flow c | Skipping knees & elbows | Pistol squat (right) | Push press (left) | Push press (right) | Eccentric subescapular (left) | Pull-up with rings 1 | Side to side jump | Farmer's walk (left) | Farmer's walk (right) | Rocket with weight (left) | Pistol squat (left) | Lunge | Rocket with weight (right) | Assisted pull-up | Hammer plank | Pelvis circles | Push-up with rings 1 | Closed push-ups | Skater jump | Row with rings 1 | Roll-out with rings 1 | Plank rotation | Open push-up | Hold with rings | Windmill with weight (right) | Power clean with KB | Pull-up hands together | Shoulder to shoulder | Inchworm | Turkish get up with weight (left) | Turkish get up with weight (right) | Flow d | Clap push-up | Shoulder opening on wall | American swing | Pistol squat with rings | Jumping squat with weight | Isometric in L1 | Bench step up with weight | 1 leg deadlift with KB (left) | Lateral push-up | 1 leg deadlift with KB (right) | Windmill with weight (left) | Push-up with roll | Turkish get-ups (right) | Squat with rings | Windmill plank | Weighted forward lunge | Bulgarian squat with weight (left) | Knees to elbows | Turkish get-ups (left) | Trx pull-ups | Thruster with KB | Tiger push-up | Isometric squat | Extended leg backroll | Side plank with knee (right) | Bulgarian squat with weigth (right) | Chin to chest | Neck strecht | Australian pull-up with box and trx | Pivot lunges (right) | Mountain climbers | Reverse lunges with extension (right) | Side plank with knee (left) | Pivot lunges (left) | Reverse lunges with extension (left) | Flow e | Shoulder circles | Double row trx | Rear delt fly 1 | Open row trx | Circles of knees together | Tricep extension | Shoulder taps | Vertical ring push-up 1 | Crossed foot to hand | Thruster with KB (right) | Leg raises 1 | Weighted Front Squats | Backroll | Kneeling to standing | Press trx | Pecs minor stretch (right) | Pecs minor stretch (left) | Fly | Thoracic rotations on knees (left) | Thoracic rotations on kness (right) | Face pull | Hamstring stretching (left) | Eccentric subscapular (right) | Hamstring stretching (right) | External rotators (right) | External rotators (left) | Plank with rings | Thoracic extensions | Bulgarian squat with rings (right) | Deficit push-up | Cat to dog | Bulgarian squat with rings (left) | High squat | Cat segmentations | Leg raises to inverted hang 1 | Neck circles | Thruster with KB (left) | Clapping push-up | Elbow and wrist circles | Bodyweight tríceps extension | Bicep curl 1 | Alternating mountain climber | Jumping lunges (left) | Jumping lunges (right) | Open lunges (right) | Body saws with TRX | Push press | Jump rope | Inclined push-up | Archer push-up 1 | L push-up | Segmented wall bends | Jumping pull-up | Windmill | Open lunges (left) | Hanging leg twist | Nordic curl | Double eights | Abductor stretching | Squat spine rotations | Short run | Swing digs | Lateral knee push-up | Jumping lunge with weight | Neck circumductions | Thoracic rotations (left) | Archer chin-up 1 | Chest fly 1 | Reverse spider push-up | Surfer | Trx pistol (left) | Isometric knee raises | Shoulder clean | Seated lateralizations | Sitting in seiza | Declined push-up | Box jump | Trx pistol (right) | Wide squat | Hip thrust | Sun hug | Turning row trx | OH lunges with weight (right) | OH lunges with weight (left) | Folding table | Forward lunges to balance (left) | Inverted tuck to chin-up | Forward lunges to balance (right) | Segmented wall extensions | Bridge segmentations | L Ring dips | Assisted chin-ups | Tucked frontlever pull-up 1 | Deadlift | Scapular pushups | Inertial rotations | Folding and extending with squat | Front squat with weight | Backward lunge with extension | L-sit roll to chin-up | Get up! | Suspended bíceps exercise | Inchworm with push-up | Hip lift with rings | Elbows to floor in squat | Archer row 1 | Knee squat | L-push-up | Skin the cat 1 | Jump chin up | Sit-up with weight | Seated hip rotations | Hanging lateral knee raises | Chin ups | Asymmetrical plank | Ankle circles | Face pull 1 | False grip pull-up | Assisted muscle-up | Ring dips 3 | One leg bridge | Ring dips 2 | Shoulder dislocations with band | Chest circumductions | Pull-up with rings 3 | Leg raise folded knees | Balancing front lunge | Bicep curl 2 | False grip flexed hang | Push-up with rings 3 | Rolling push-up | Pull-up with rings 2 | Row with rings 3 | Pistol squat trx | Farmer's Walk (Left side) | Thruster with kettlebell left | Jump | Vertical ring push-up 2 | False grip hang | Windmill push-up | Farmer's Walk (Right side) | Tricep dip | Mountain climber frog | Row with rings 2 | Leg raises to inverted hang 2 | Archer chin-up 2 | Tuck shoulder stand 1 | Mountain push-up | Push-up with rings 2 | Knight lunges (right) | Knight lunges (left) | L-sit with rings 3 | Skin the cat 2 | Separate knee circles | Supine hang bar | Pelvic tilting circles | Lumbar circumductions | Chest expansions | Deficit L push-up | Clean and jerk | Chest fly 2 | Mountain climber with rotation (right) | Mountain climber with rotation (left) | Roll-out with rings 3 | Roll-out with rings 2 | Toes to bar | Tiger mckenzie | Diagonal Climber | Parallel Squat | Sit-up with extension | Hip plank | Leg raises 3 | Freestyle | Tuck hold to tuck shoulder stand | Plank press | Tucked frontlever pull-up 2 | Farmer walk | Tiger | Turkish get-ups with weight (right) | Underswitch | Assisted pistol squat (right) | Side to side jump squat | Turkish get-ups with weight (left) | Assisted pistol squat with box | Assisted pistol squat (left) | 1 leg deadlift | Medium Skips | Back | 1 leg dead lift 1with KB (right) | Leg raises 2 | L-sit with rings 2 | High Skips | Clapping knee pushup | Archer row 2 | Burpee roll | Tuck shoulder stand 2 | Double burpee | Knee diamond push-up | Spiderman | Seiza knees transition | Open knee push-up | Multijumps | 1 leg dead lift with KB (left) | Knee clap push-up | Two feet mountain climber | Clamshell | Face pull 2 | Plank hand to opposite foot | Push-up climber | Abdomen rowler | Rocket back | Hollow legs | Pull-up with table | Spiderman Squat | Muscle-up 1 | Seated squat trx | Crunch with hip lock | Underside kick | Oblique with foot support | Isometric supine hand-knee | Kneeling squat | Hip boxing | Cross jacks | Stride backward | Diagonal crunch | Stride forward | Stride front to back | Quadruped Superman | Bulgarian squat with weight (right) | Assisted pistol squat | Assisted push-up | Assisted squat | Two feet hip thrust | Isometric bridge with weight | Wrist flexion and extension | Single leg hip thrust | Knee push-up hand lift | Mountain climber plank | Gluteal fan | Lateral lunge with drop | Lateral mountain climber | Frontal mountain climber | Reverse spider knee push-up | Lateral squat | Star abs | Open lunge | Bubu | Hindu knee push-up | Oblique with knee support | Clamshell with knee extension | Alternate Superman | Inverted foot to hand | Hollow | Alternating overhead plank | 1 leg dead lift with KB | Alternating shoulder press | Jumping lunges with weight (left) | Jumping lunges with weight (right) | Diagonals | Muscle-up 2 | Leg raise on floor | Windmill paleo | Rocket | Pivot lunge | Walk | Half clean | Bulgarian squat | OH lunges with weight | Clock push-up | Hip thrust with weight | Deficit handstand push-up | Burpee pull-ups | Foot to hand | Sentadas | Dynamic frontal hip stretch | Zancadas | Left foot to hand cross | Reptile knee push-up | Burpee with knee to elbows jump | Right foot to hand cross | Hand-to-hand circles | Supporting elbow circles | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 1905740 | 570990 | 56712 | 48597 | 47546 | 42711 | 34216 | 34122 | 32149 | 27617 | 25570 | 23198 | 22000 | 18795 | 18727 | 15455 | 14886 | 14857 | 14331 | 13763 | 13465 | 12817 | 12379 | 11889 | 11214 | 9604 | 9597 | 9539 | 9461 | 9111 | 9012 | 8381 | 8340 | 8226 | 8198 | 8179 | 8084 | 8012 | 7935 | 7772 | 7760 | 7409 | 7265 | 7240 | 7148 | 7066 | 7000 | 6740 | 6728 | 6652 | 6630 | 6607 | 6426 | 6426 | 6385 | 6244 | 6085 | 5828 | 5807 | 5644 | 5555 | 5366 | 5307 | 5296 | 5231 | 5196 | 5115 | 5062 | 5034 | 4902 | 4837 | 4813 | 4666 | 4549 | 4485 | 4444 | 4438 | 4437 | 4429 | 4367 | 4350 | 4284 | 4251 | 4180 | 4173 | 3837 | 3774 | 3769 | 3709 | 3657 | 3597 | 3536 | 3528 | 3467 | 3409 | 3401 | 3372 | 3279 | 3272 | 3236 | 3227 | 3196 | 3192 | 3173 | 3168 | 3140 | 3121 | 3120 | 3077 | 3061 | 2961 | 2957 | 2892 | 2890 | 2882 | 2872 | 2837 | 2777 | 2715 | 2715 | 2696 | 2683 | 2671 | 2657 | 2640 | 2615 | 2602 | 2591 | 2579 | 2544 | 2527 | 2522 | 2520 | 2520 | 2519 | 2512 | 2491 | 2479 | 2456 | 2422 | 2374 | 2371 | 2369 | 2359 | 2353 | 2351 | 2344 | 2323 | 2299 | 2292 | 2248 | 2248 | 2240 | 2237 | 2222 | 2201 | 2188 | 2172 | 2144 | 2136 | 2074 | 2060 | 2041 | 2000 | 1995 | 1987 | 1980 | 1944 | 1910 | 1904 | 1834 | 1831 | 1788 | 1768 | 1734 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1671 | 1667 | 1662 | 1637 | 1634 | 1596 | 1569 | 1569 | 1560 | 1551 | 1524 | 1517 | 1515 | 1471 | 1462 | 1460 | 1409 | 1398 | 1394 | 1374 | 1373 | 1372 | 1370 | 1361 | 1354 | 1332 | 1326 | 1321 | 1316 | 1313 | 1250 | 1225 | 1223 | 1214 | 1182 | 1182 | 1149 | 1146 | 1139 | 1124 | 1096 | 1091 | 1074 | 1065 | 1060 | 1057 | 1051 | 1046 | 1046 | 1044 | 1036 | 1024 | 1020 | 1004 | 1004 | 993 | 968 | 968 | 947 | 946 | 945 | 937 | 915 | 915 | 909 | 907 | 897 | 892 | 888 | 888 | 888 | 882 | 880 | 868 | 840 | 773 | 763 | 763 | 731 | 720 | 714 | 651 | 629 | 626 | 614 | 610 | 601 | 594 | 579 | 523 | 515 | 508 | 484 | 472 | 472 | 451 | 444 | 444 | 441 | 436 | 426 | 422 | 411 | 408 | 399 | 397 | 393 | 384 | 382 | 380 | 380 | 375 | 375 | 372 | 368 | 363 | 363 | 362 | 352 | 344 | 343 | 333 | 328 | 315 | 315 | 314 | 312 | 305 | 305 | 305 | 305 | 305 | 296 | 289 | 288 | 285 | 285 | 284 | 280 | 265 | 262 | 255 | 245 | 240 | 235 | 234 | 230 | 230 | 215 | 213 | 208 | 204 | 202 | 195 | 195 | 194 | 191 | 190 | 187 | 186 | 186 | 172 | 171 | 171 | 166 | 166 | 165 | 161 | 160 | 156 | 151 | 146 | 145 | 144 | 144 | 142 | 139 | 136 | 132 | 127 | 127 | 117 | 116 | 113 | 112 | 111 | 106 | 103 | 102 | 102 | 98 | 96 | 95 | 93 | 93 | 88 | 88 | 85 | 82 | 81 | 79 | 77 | 77 | 74 | 70 | 70 | 69 | 67 | 66 | 66 | 66 | 65 | 63 | 62 | 58 | 57 | 56 | 52 | 50 | 46 | 46 | 44 | 41 | 37 | 37 | 36 | 29 | 29 | 28 | 25 | 24 | 24 | 22 | 22 | 22 | 21 | 20 | 17 | 17 | 16 | 12 | 12 | 9 | 9 | 5 | 5 | 4 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 2 |
| Percent | 100.0% | 29.96% | 2.98% | 2.55% | 2.49% | 2.24% | 1.8% | 1.79% | 1.69% | 1.45% | 1.34% | 1.22% | 1.15% | 0.99% | 0.98% | 0.81% | 0.78% | 0.78% | 0.75% | 0.72% | 0.71% | 0.67% | 0.65% | 0.62% | 0.59% | 0.5% | 0.5% | 0.5% | 0.5% | 0.48% | 0.47% | 0.44% | 0.44% | 0.43% | 0.43% | 0.43% | 0.42% | 0.42% | 0.42% | 0.41% | 0.41% | 0.39% | 0.38% | 0.38% | 0.38% | 0.37% | 0.37% | 0.35% | 0.35% | 0.35% | 0.35% | 0.35% | 0.34% | 0.34% | 0.34% | 0.33% | 0.32% | 0.31% | 0.3% | 0.3% | 0.29% | 0.28% | 0.28% | 0.28% | 0.27% | 0.27% | 0.27% | 0.27% | 0.26% | 0.26% | 0.25% | 0.25% | 0.24% | 0.24% | 0.24% | 0.23% | 0.23% | 0.23% | 0.23% | 0.23% | 0.23% | 0.22% | 0.22% | 0.22% | 0.22% | 0.2% | 0.2% | 0.2% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.18% | 0.18% | 0.18% | 0.18% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.16% | 0.16% | 0.16% | 0.16% | 0.16% | 0.16% | 0.16% | 0.15% | 0.15% | 0.15% | 0.15% | 0.15% | 0.15% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.14% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
Looking at name_en_exercises, we can see that most of the exercises executed had been REST (30%), and then KNEE PUSH-UP (3%). Now, it is seen that it would be sensible, to check this data without REST exercise.
| Total | 3.5 | 3.8 | 2.5 | 3.0 | 3.2 | 4.0 | 2.3 | 2.8 | 5.0 | 4.2 | 2.6 | 5.2 | 3.9 | 3.6 | 23.0 | 5.5 | 12.0 | 2.9 | 4.5 | 8.0 | 2.0 | 6.0 | 4.8 | 1.0 | 4.3 | 5.3 | 7.0 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 1334750 | 278906 | 205123 | 150585 | 116442 | 97140 | 85732 | 78730 | 76550 | 60891 | 54420 | 36266 | 19414 | 19012 | 17007 | 15455 | 4743 | 4444 | 3528 | 3123 | 2695 | 1982 | 909 | 890 | 368 | 213 | 160 | 22 |
| Percent | 100.0% | 20.9% | 15.37% | 11.28% | 8.72% | 7.28% | 6.42% | 5.9% | 5.74% | 4.56% | 4.08% | 2.72% | 1.45% | 1.42% | 1.27% | 1.16% | 0.36% | 0.33% | 0.26% | 0.23% | 0.2% | 0.15% | 0.07% | 0.07% | 0.03% | 0.02% | 0.01% | 0.0% |
When excluding exercise with name rest and taking met_multiplier as a categorical variable, it can be seen than most frequent MET value is 3.5 (21%).
| Total | Knee push-up | Pull-up | Squat | Paleo sit-up | Burpee | Push-up | Dips | Skipping | Bridge | Lunges (right) | Lunges (left) | Jumping squat | Free thruster | Sprint | Side lunge | Chin up | Plank pivot | Wall climb | Leg raises | Superman | Leg lifts | Jumping jacks | Plank balance | Side to side squat | Mckenzie | Plank | Glute march | Diamond push-up | Plank spider | Semi burpee | Sit-up | Windshield wiper | Flow a | Mountain runner | Hindu push-up | Bulgarian squat (left) | Bulgarian squat (right) | Diver | Suspended row | Backward lunge | Pallof press (left) | Handstand push-up | Isometric bridge | Mountain climber | Pallof press (right) | V sit-up | Swings | 1 leg bridge (left) | 1 leg bridge (right) | Horizontal jump | Mountain climbers up | Forward lunge | Semi V sit-up | Jumping lunge | Donkey kicks | Rocket (right) | Mountain climbers down | Rocket (left) | Plank taps (shoulder, hip, knee, ankle) | Shoulder swimmers | Side plank (right) | Push-up with hand lift | 1 leg dead lift (right) | 1 leg dead lift (left) | Forward thrust | Deck squat | Flow b | Russian twist | Press (right) | Side plank (left) | Press (left) | Australian pull-up | Weighted backward lunge | Double jump rope | Row (left) | Assisted pistol squat with box (right) | Row (right) | Burrol | Goblet squat | Assisted pistol squat with box (left) | Reptile push-up | 2 legs half burpee | Spider push-up | Star jump | Clean (left) | Clean (right) | Plank extension | Ring dips 1 | Weighted side lunge | Flow c | Skipping knees & elbows | Pistol squat (right) | Push press (left) | Push press (right) | Eccentric subescapular (left) | Pull-up with rings 1 | Side to side jump | Farmer's walk (left) | Farmer's walk (right) | Rocket with weight (left) | Pistol squat (left) | Lunge | Rocket with weight (right) | Assisted pull-up | Hammer plank | Pelvis circles | Push-up with rings 1 | Closed push-ups | Skater jump | Row with rings 1 | Roll-out with rings 1 | Plank rotation | Open push-up | Hold with rings | Windmill with weight (right) | Power clean with KB | Shoulder to shoulder | Pull-up hands together | Inchworm | Turkish get up with weight (left) | Turkish get up with weight (right) | Flow d | Clap push-up | Shoulder opening on wall | American swing | Pistol squat with rings | Jumping squat with weight | Isometric in L1 | Bench step up with weight | 1 leg deadlift with KB (left) | 1 leg deadlift with KB (right) | Lateral push-up | Windmill with weight (left) | Push-up with roll | Turkish get-ups (right) | Squat with rings | Windmill plank | Weighted forward lunge | Bulgarian squat with weight (left) | Knees to elbows | Turkish get-ups (left) | Trx pull-ups | Thruster with KB | Tiger push-up | Isometric squat | Extended leg backroll | Side plank with knee (right) | Bulgarian squat with weigth (right) | Chin to chest | Neck strecht | Australian pull-up with box and trx | Pivot lunges (right) | Mountain climbers | Reverse lunges with extension (right) | Side plank with knee (left) | Pivot lunges (left) | Reverse lunges with extension (left) | Flow e | Shoulder circles | Double row trx | Rear delt fly 1 | Open row trx | Circles of knees together | Tricep extension | Shoulder taps | Vertical ring push-up 1 | Crossed foot to hand | Thruster with KB (right) | Leg raises 1 | Weighted Front Squats | Backroll | Kneeling to standing | Press trx | Hamstring stretching (left) | External rotators (left) | Thoracic rotations on kness (right) | Fly | Hamstring stretching (right) | Eccentric subscapular (right) | Thoracic rotations on knees (left) | Face pull | Pecs minor stretch (left) | Pecs minor stretch (right) | External rotators (right) | Plank with rings | Thoracic extensions | Bulgarian squat with rings (right) | Deficit push-up | Cat to dog | Bulgarian squat with rings (left) | Cat segmentations | High squat | Leg raises to inverted hang 1 | Neck circles | Thruster with KB (left) | Clapping push-up | Elbow and wrist circles | Bodyweight tríceps extension | Bicep curl 1 | Alternating mountain climber | Jumping lunges (left) | Jumping lunges (right) | Open lunges (right) | Body saws with TRX | Push press | Jump rope | Inclined push-up | Archer push-up 1 | L push-up | Segmented wall bends | Jumping pull-up | Windmill | Open lunges (left) | Hanging leg twist | Nordic curl | Double eights | Abductor stretching | Squat spine rotations | Swing digs | Short run | Lateral knee push-up | Jumping lunge with weight | Neck circumductions | Thoracic rotations (left) | Archer chin-up 1 | Chest fly 1 | Reverse spider push-up | Surfer | Trx pistol (left) | Isometric knee raises | Shoulder clean | Seated lateralizations | Sitting in seiza | Declined push-up | Box jump | Trx pistol (right) | Wide squat | Sun hug | Hip thrust | Turning row trx | OH lunges with weight (left) | OH lunges with weight (right) | Folding table | Forward lunges to balance (left) | Inverted tuck to chin-up | Forward lunges to balance (right) | Segmented wall extensions | Bridge segmentations | L Ring dips | Assisted chin-ups | Tucked frontlever pull-up 1 | Deadlift | Folding and extending with squat | Scapular pushups | Inertial rotations | Front squat with weight | Backward lunge with extension | L-sit roll to chin-up | Get up! | Suspended bíceps exercise | Inchworm with push-up | Hip lift with rings | Elbows to floor in squat | Archer row 1 | Knee squat | L-push-up | Skin the cat 1 | Jump chin up | Sit-up with weight | Seated hip rotations | Hanging lateral knee raises | Chin ups | Asymmetrical plank | Ankle circles | Face pull 1 | False grip pull-up | Assisted muscle-up | Ring dips 3 | One leg bridge | Ring dips 2 | Chest circumductions | Shoulder dislocations with band | Pull-up with rings 3 | Leg raise folded knees | Balancing front lunge | Bicep curl 2 | False grip flexed hang | Push-up with rings 3 | Rolling push-up | Pull-up with rings 2 | Row with rings 3 | Pistol squat trx | Farmer's Walk (Left side) | Thruster with kettlebell left | Jump | Vertical ring push-up 2 | False grip hang | Windmill push-up | Farmer's Walk (Right side) | Tricep dip | Mountain climber frog | Row with rings 2 | Leg raises to inverted hang 2 | Archer chin-up 2 | Tuck shoulder stand 1 | Mountain push-up | Push-up with rings 2 | Knight lunges (right) | Knight lunges (left) | L-sit with rings 3 | Skin the cat 2 | Supine hang bar | Chest expansions | Pelvic tilting circles | Separate knee circles | Lumbar circumductions | Deficit L push-up | Clean and jerk | Chest fly 2 | Mountain climber with rotation (left) | Mountain climber with rotation (right) | Roll-out with rings 3 | Roll-out with rings 2 | Toes to bar | Tiger mckenzie | Diagonal Climber | Parallel Squat | Sit-up with extension | Hip plank | Leg raises 3 | Freestyle | Tuck hold to tuck shoulder stand | Plank press | Tucked frontlever pull-up 2 | Farmer walk | Tiger | Turkish get-ups with weight (right) | Assisted pistol squat (right) | Underswitch | Side to side jump squat | Turkish get-ups with weight (left) | Assisted pistol squat with box | Assisted pistol squat (left) | Medium Skips | 1 leg deadlift | Back | 1 leg dead lift 1with KB (right) | Leg raises 2 | L-sit with rings 2 | High Skips | Clapping knee pushup | Archer row 2 | Burpee roll | Tuck shoulder stand 2 | Double burpee | Knee diamond push-up | Spiderman | Seiza knees transition | Open knee push-up | Multijumps | 1 leg dead lift with KB (left) | Knee clap push-up | Two feet mountain climber | Clamshell | Face pull 2 | Plank hand to opposite foot | Push-up climber | Abdomen rowler | Rocket back | Hollow legs | Pull-up with table | Spiderman Squat | Muscle-up 1 | Seated squat trx | Crunch with hip lock | Underside kick | Oblique with foot support | Kneeling squat | Isometric supine hand-knee | Hip boxing | Cross jacks | Stride backward | Diagonal crunch | Stride forward | Stride front to back | Quadruped Superman | Bulgarian squat with weight (right) | Assisted pistol squat | Assisted squat | Assisted push-up | Two feet hip thrust | Isometric bridge with weight | Single leg hip thrust | Wrist flexion and extension | Knee push-up hand lift | Mountain climber plank | Gluteal fan | Lateral lunge with drop | Lateral mountain climber | Frontal mountain climber | Reverse spider knee push-up | Lateral squat | Star abs | Open lunge | Bubu | Hindu knee push-up | Oblique with knee support | Alternate Superman | Clamshell with knee extension | Inverted foot to hand | Alternating overhead plank | Hollow | 1 leg dead lift with KB | Alternating shoulder press | Jumping lunges with weight (right) | Jumping lunges with weight (left) | Leg raise on floor | Muscle-up 2 | Diagonals | Windmill paleo | Rocket | Walk | Pivot lunge | Half clean | Bulgarian squat | OH lunges with weight | Clock push-up | Hip thrust with weight | Deficit handstand push-up | Burpee pull-ups | Foot to hand | Dynamic frontal hip stretch | Sentadas | Zancadas | Hand-to-hand circles | Burpee with knee to elbows jump | Supporting elbow circles | Left foot to hand cross | Right foot to hand cross | Reptile knee push-up | Rest | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 1334750 | 56712 | 48597 | 47546 | 42711 | 34216 | 34122 | 32149 | 27617 | 25570 | 23198 | 22000 | 18795 | 18727 | 15455 | 14886 | 14857 | 14331 | 13763 | 13465 | 12817 | 12379 | 11889 | 11214 | 9604 | 9597 | 9539 | 9461 | 9111 | 9012 | 8381 | 8340 | 8226 | 8198 | 8179 | 8084 | 8012 | 7935 | 7772 | 7760 | 7409 | 7265 | 7240 | 7148 | 7066 | 7000 | 6740 | 6728 | 6652 | 6630 | 6607 | 6426 | 6426 | 6385 | 6244 | 6085 | 5828 | 5807 | 5644 | 5555 | 5366 | 5307 | 5296 | 5231 | 5196 | 5115 | 5062 | 5034 | 4902 | 4837 | 4813 | 4666 | 4549 | 4485 | 4444 | 4438 | 4437 | 4429 | 4367 | 4350 | 4284 | 4251 | 4180 | 4173 | 3837 | 3774 | 3769 | 3709 | 3657 | 3597 | 3536 | 3528 | 3467 | 3409 | 3401 | 3372 | 3279 | 3272 | 3236 | 3227 | 3196 | 3192 | 3173 | 3168 | 3140 | 3121 | 3120 | 3077 | 3061 | 2961 | 2957 | 2892 | 2890 | 2882 | 2872 | 2837 | 2777 | 2715 | 2715 | 2696 | 2683 | 2671 | 2657 | 2640 | 2615 | 2602 | 2591 | 2579 | 2544 | 2527 | 2522 | 2520 | 2520 | 2519 | 2512 | 2491 | 2479 | 2456 | 2422 | 2374 | 2371 | 2369 | 2359 | 2353 | 2351 | 2344 | 2323 | 2299 | 2292 | 2248 | 2248 | 2240 | 2237 | 2222 | 2201 | 2188 | 2172 | 2144 | 2136 | 2074 | 2060 | 2041 | 2000 | 1995 | 1987 | 1980 | 1944 | 1910 | 1904 | 1834 | 1831 | 1788 | 1768 | 1734 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1686 | 1671 | 1667 | 1662 | 1637 | 1634 | 1596 | 1569 | 1569 | 1560 | 1551 | 1524 | 1517 | 1515 | 1471 | 1462 | 1460 | 1409 | 1398 | 1394 | 1374 | 1373 | 1372 | 1370 | 1361 | 1354 | 1332 | 1326 | 1321 | 1316 | 1313 | 1250 | 1225 | 1223 | 1214 | 1182 | 1182 | 1149 | 1146 | 1139 | 1124 | 1096 | 1091 | 1074 | 1065 | 1060 | 1057 | 1051 | 1046 | 1046 | 1044 | 1036 | 1024 | 1020 | 1004 | 1004 | 993 | 968 | 968 | 947 | 946 | 945 | 937 | 915 | 915 | 909 | 907 | 897 | 892 | 888 | 888 | 888 | 882 | 880 | 868 | 840 | 773 | 763 | 763 | 731 | 720 | 714 | 651 | 629 | 626 | 614 | 610 | 601 | 594 | 579 | 523 | 515 | 508 | 484 | 472 | 472 | 451 | 444 | 444 | 441 | 436 | 426 | 422 | 411 | 408 | 399 | 397 | 393 | 384 | 382 | 380 | 380 | 375 | 375 | 372 | 368 | 363 | 363 | 362 | 352 | 344 | 343 | 333 | 328 | 315 | 315 | 314 | 312 | 305 | 305 | 305 | 305 | 305 | 296 | 289 | 288 | 285 | 285 | 284 | 280 | 265 | 262 | 255 | 245 | 240 | 235 | 234 | 230 | 230 | 215 | 213 | 208 | 204 | 202 | 195 | 195 | 194 | 191 | 190 | 187 | 186 | 186 | 172 | 171 | 171 | 166 | 166 | 165 | 161 | 160 | 156 | 151 | 146 | 145 | 144 | 144 | 142 | 139 | 136 | 132 | 127 | 127 | 117 | 116 | 113 | 112 | 111 | 106 | 103 | 102 | 102 | 98 | 96 | 95 | 93 | 93 | 88 | 88 | 85 | 82 | 81 | 79 | 77 | 77 | 74 | 70 | 70 | 69 | 67 | 66 | 66 | 66 | 65 | 63 | 62 | 58 | 57 | 56 | 52 | 50 | 46 | 46 | 44 | 41 | 37 | 37 | 36 | 29 | 29 | 28 | 25 | 24 | 24 | 22 | 22 | 22 | 21 | 20 | 17 | 17 | 16 | 12 | 12 | 9 | 9 | 5 | 5 | 4 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 0 |
| Percent | 100.0% | 4.25% | 3.64% | 3.56% | 3.2% | 2.56% | 2.56% | 2.41% | 2.07% | 1.92% | 1.74% | 1.65% | 1.41% | 1.4% | 1.16% | 1.12% | 1.11% | 1.07% | 1.03% | 1.01% | 0.96% | 0.93% | 0.89% | 0.84% | 0.72% | 0.72% | 0.71% | 0.71% | 0.68% | 0.68% | 0.63% | 0.62% | 0.62% | 0.61% | 0.61% | 0.61% | 0.6% | 0.59% | 0.58% | 0.58% | 0.56% | 0.54% | 0.54% | 0.54% | 0.53% | 0.52% | 0.5% | 0.5% | 0.5% | 0.5% | 0.49% | 0.48% | 0.48% | 0.48% | 0.47% | 0.46% | 0.44% | 0.44% | 0.42% | 0.42% | 0.4% | 0.4% | 0.4% | 0.39% | 0.39% | 0.38% | 0.38% | 0.38% | 0.37% | 0.36% | 0.36% | 0.35% | 0.34% | 0.34% | 0.33% | 0.33% | 0.33% | 0.33% | 0.33% | 0.33% | 0.32% | 0.32% | 0.31% | 0.31% | 0.29% | 0.28% | 0.28% | 0.28% | 0.27% | 0.27% | 0.26% | 0.26% | 0.26% | 0.26% | 0.25% | 0.25% | 0.25% | 0.25% | 0.24% | 0.24% | 0.24% | 0.24% | 0.24% | 0.24% | 0.24% | 0.23% | 0.23% | 0.23% | 0.23% | 0.22% | 0.22% | 0.22% | 0.22% | 0.22% | 0.22% | 0.21% | 0.21% | 0.2% | 0.2% | 0.2% | 0.2% | 0.2% | 0.2% | 0.2% | 0.2% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.19% | 0.18% | 0.18% | 0.18% | 0.18% | 0.18% | 0.18% | 0.18% | 0.18% | 0.18% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.17% | 0.16% | 0.16% | 0.16% | 0.16% | 0.16% | 0.16% | 0.15% | 0.15% | 0.15% | 0.15% | 0.15% | 0.15% | 0.15% | 0.14% | 0.14% | 0.14% | 0.14% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.13% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.11% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.09% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.06% | 0.06% | 0.06% | 0.06% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
Most frequent exercise done is KNEE PUSH-UP (4.25%), then PULL-UP (3.64%) and SQUAT (3.56%).
Taking into consideration only exercises, we can look into
Calories are not taken into consideration, because for every user the calories value for an exercise is different. It is possible to create an average for each exercise. So we want to keep value of each exercise for all users. This variable will be named as avg_calories_for_exercise.
Below there are descriptive statistics of met_multiplier_exercises and avg_calories_for_exercises.
| count | mean | std | min | 25% | 50% | 75% | max | var | skewness | kurtosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| met_multiplier_exercises | 472.00 | 3.45 | 1.40 | 1.00 | 2.50 | 3.50 | 3.92 | 23.00 | 1.97 | 6.56 | 82.70 |
| avg_calories_for_exercise | 472.00 | 3.14 | 1.62 | 0.31 | 2.00 | 2.94 | 3.98 | 12.60 | 2.62 | 1.36 | 4.02 |
When met_multiplier_exercises will be taken into consideration as numerical variable, the mean value for all exercises is 3.45 (SD 1.4), that means most of the exercises have Moderate-Intensity Activity level. Maximum value is 23, which is Vigorous-Intensity Activity exercise (it is sprint). For avg_calories_for_exercises, mean number of average burned calories for all exercises is 3.14 (SD 1.6). Maximum value of average burned calories is 12.6 (it is a sprint).
Again, the distribution of data will be checked for every variable. Goodness of fit will depend on RSS.
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.03 sec] [RSS: 0.131817] [loc=3.500 scale=0.780] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=0.967948, loc=3.5, scale=0.78027)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[gamma] [0.01 sec] [RSS: 0.0391767] [loc=-0.036 scale=0.800] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngamma\nRSS(a=3.9732, loc=-0.0360021, scale=0.799698)'}, xlabel='Values', ylabel='Frequency'>)
The data don't follow normal distribution.
For categorical data only met_multiplier variable will be taken into consideration. Below there are frequency table and plot for this variable.
| Total | 3.5 | 2.3 | 3.8 | 4.0 | 3.2 | 2.5 | 3.0 | 4.2 | 2.8 | 5.0 | 2.0 | 3.6 | 5.2 | 2.6 | 1.0 | 3.9 | 6.0 | 5.5 | 8.0 | 4.5 | 4.8 | 4.3 | 5.3 | 7.0 | 12.0 | 23.0 | 2.9 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 472 | 62 | 58 | 56 | 52 | 46 | 42 | 23 | 19 | 19 | 14 | 13 | 10 | 9 | 9 | 8 | 7 | 6 | 4 | 4 | 3 | 2 | 1 | 1 | 1 | 1 | 1 | 1 |
| Percent | 100.0% | 13.14% | 12.29% | 11.86% | 11.02% | 9.75% | 8.9% | 4.87% | 4.03% | 4.03% | 2.97% | 2.75% | 2.12% | 1.91% | 1.91% | 1.69% | 1.48% | 1.27% | 0.85% | 0.85% | 0.64% | 0.42% | 0.21% | 0.21% | 0.21% | 0.21% | 0.21% | 0.21% |
Most of the exercises have MET equal to 3.5 (Moderate-Intensity Activity), then 2.3 (Light-Intensity Activity).
For users we will take into consideration:
As numerical data, variables:
will be taken into consideration. Also, body_fat and training_days_setting will be taken as categorical variable in the later part.
| count | mean | std | min | 25% | 50% | 75% | max | var | skewness | kurtosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| height | 3172.00 | 171.45 | 9.09 | 142.00 | 165.00 | 172.00 | 178.00 | 198.00 | 82.67 | -0.07 | -0.48 |
| weight | 3172.00 | 71.55 | 13.76 | 40.00 | 61.00 | 71.00 | 80.00 | 147.00 | 189.31 | 0.62 | 0.80 |
| points | 3172.00 | 63432.65 | 177832.66 | 0.00 | 387.50 | 3700.00 | 45653.25 | 2749450.00 | 31624455298.06 | 6.61 | 63.70 |
| best_weekly_streak_users | 3172.00 | 4.73 | 6.45 | 1.00 | 1.00 | 2.00 | 5.00 | 49.00 | 41.54 | 3.15 | 12.38 |
| total_sessions_users2 | 3172.00 | 15.58 | 25.02 | 1.00 | 2.00 | 5.00 | 18.00 | 311.00 | 625.88 | 3.43 | 18.38 |
| total_time_users2 | 3172.00 | 21097.86 | 36572.68 | 18.00 | 1830.75 | 5685.50 | 22869.25 | 471782.80 | 1337560896.46 | 3.62 | 21.50 |
| total_reps_users2 | 3172.00 | 4008.79 | 7481.15 | 8.00 | 375.50 | 1061.50 | 4221.75 | 120390.00 | 55967531.02 | 4.87 | 41.27 |
| reps_per_session_users2 | 3172.00 | 221.08 | 84.64 | 8.00 | 167.06 | 219.00 | 267.00 | 670.10 | 7164.68 | 0.60 | 1.47 |
| total_calories_users2 | 3172.00 | 1293.90 | 2340.82 | 0.87 | 107.55 | 333.16 | 1382.42 | 31452.30 | 5479429.42 | 3.93 | 24.68 |
| kcal_per_session_users2 | 3172.00 | 70.29 | 32.64 | 0.87 | 47.54 | 66.77 | 87.93 | 297.64 | 1065.05 | 1.33 | 4.58 |
| BMI | 3172.00 | 24.23 | 3.69 | 13.78 | 21.78 | 23.66 | 25.95 | 48.55 | 13.62 | 1.20 | 2.80 |
There are 3172 users in a database. Mean value of height among the users is 171.5 cm (SD 9.09), median is 172 cm (IQR 165 - 178). The shortest person is 142 cm tall and the tallest person is 198 cm tall. Mean weight of the user is 71.55 kg (SD 13.76) and median is 71 kg (61 - 80). The heaviest person has 147 kg and the lightest - 40 kg. When it comes to the body_fat, mean value is 23.5% (SD 8.1), median is 20% (IQR 20 - 30). Maximum value of body fat is 50% and minimum is 6%. Mean value of number of days in a week setting is 3.6 days (SD 1.3), median is 3 days (IQR 3 - 4), minimum is 1 day a week and maximum is 7 days a week. Mean value of points is 63432 (SD 177833), median is 3700 points (IQR 388 - 45653). Maximum value of points is 2749450. Mean best_weakly_streak among users is 4.73 weeks (SD 6.45), median is 2 weeks (IQR 1 - 5). Minimum value is one week and maximum is 49 weeks. Unfortunately, because of previous data cleaning, a lot of exercise rows were deleted and now, this variable is not fully correct. Mean value of total number of sessions executed is 16 sessions (SD 25), median is 5 sessions (IQR 2 - 18) and maximum number of sessions is 311. Variable total_time_users2 is given in seconds. It is a value that says how much time did a user spend on all of the sessions (and exercises). Average is 21098 seconds (~ 352 minutes, almost 6 hours) (SD 36573), median is 5686 seconds (~ 95 minutes) (IQR 1831 - 22669). Maximum time of total time is 471783 seconds (~7863 minutes, 131 hours). Mean of total_reps (all of the reps users did in all of the exercises and sessions) is 4009 reps (SD 7481), median is 1062 reps (IQR 376 - 4222). Maximum number of reps done is 120390 reps. Every user has calculated average number of reps made in session. Mean value of this average is 221 reps (in a session) (SD 85), median is 219 (IQR 167 - 267). Maximum average of reps in a session is 670. Total number of calories (total_calories) is number of calories that user burned in all of the sessions. Mean number is 1294 calories (SD 2341), median is 333 calories (IQR 108 - 1382). Maximum value of burned calories is 31452. Kcal_per_session says how many calories (in average) did the user burned in one session. Mean value is 70 kcal in a session (SD 33), median is 67 kcal in a session (IQR 48 - 88). Maximum value is 298 kcal in average in a session. Mean value of BMI is 24.2 (SD 3.7), which is normal weight. Median id 23.7 (IQR 21.8 - 26), which is also a normal category. Minimum is 13.8 - underweight and maximum is 48.6 - which is obesity.
The distribution of data will be checked for every variable. Goodness of fit will depend on RSS.
[distfit] >fit.. [distfit] >transform.. [distfit] >[beta] [0.04 sec] [RSS: 0.00550527] [loc=136.931 scale=65.649] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nbeta\nRSS(a=6.33027, b=5.71007, loc=136.931, scale=65.6486)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[beta] [0.05 sec] [RSS: 0.000563108] [loc=26.783 scale=13583483.261] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nbeta\nRSS(a=10.5565, b=3.20316e+06, loc=26.7829, scale=1.35835e+07)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.03 sec] [RSS: 0.170709] [loc=22.807 scale=7.219] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=1.43264, loc=22.8066, scale=7.21901)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.02 sec] [RSS: 15.9434] [loc=3.579 scale=1.151] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=1.49804, loc=3.57946, scale=1.15081)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[expon] [0.00 sec] [RSS: 2.28453e-11] [loc=0.000 scale=63432.646] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nexpon\nRSS(loc=0, scale=63432.6)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[gamma] [0.05 sec] [RSS: 0.0140818] [loc=1.000 scale=7.415] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngamma\nRSS(a=0.459432, loc=1, scale=7.41542)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[t] [0.08 sec] [RSS: 0.00019219] [loc=2.868 scale=2.721] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nt\nRSS(df=0.701907, loc=2.86753, scale=2.7207)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[t] [0.07 sec] [RSS: 7.33549e-11] [loc=2757.460 scale=2765.171] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\nt\nRSS(df=0.612212, loc=2757.46, scale=2765.17)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[pareto] [0.04 sec] [RSS: 4.52583e-08] [loc=-0.000 scale=8.000] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\npareto\nRSS(b=0.199546, loc=-0.000423249, scale=8.00042)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.02 sec] [RSS: 1.35619e-05] [loc=215.545 scale=67.414] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=1.15417, loc=215.545, scale=67.4136)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[pareto] [0.07 sec] [RSS: 5.80005e-07] [loc=-1.831 scale=2.699] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\npareto\nRSS(b=0.184706, loc=-1.83117, scale=2.6994)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[gamma] [0.07 sec] [RSS: 1.51986e-05] [loc=-87.917 scale=5.709] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngamma\nRSS(a=27.6705, loc=-87.9166, scale=5.70947)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[genextreme] [0.09 sec] [RSS: 0.00294442] [loc=22.632 scale=2.979] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngenextreme\nRSS(c=0.0354817, loc=22.6323, scale=2.97856)'}, xlabel='Values', ylabel='Frequency'>)
The data don't follow normal distribution.
As a categorical data will be taken:
| Frequency | Percent | Cumulative Percent | ||
|---|---|---|---|---|
| Variable | factors | |||
| Gender | ||||
| female | 1217.00 | 38.37% | 38.37% | |
| male | 1955.00 | 61.63% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Activity_level | ||||
| active | 1784.00 | 56.24% | 56.24% | |
| sedentary | 1058.00 | 33.35% | 89.6% | |
| very active | 330.00 | 10.4% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Goal | ||||
| antiaging | 474.00 | 14.94% | 14.94% | |
| gain | 1445.00 | 45.55% | 60.5% | |
| lose | 1253.00 | 39.5% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Language | ||||
| en | 177.00 | 5.58% | 5.58% | |
| es | 2995.00 | 94.42% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Body_type | ||||
| mid | 1501.00 | 47.32% | 47.32% | |
| strong | 281.00 | 8.86% | 56.18% | |
| thin | 1390.00 | 43.82% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| BMI_category | ||||
| Normal | 2053.00 | 64.72% | 64.72% | |
| Obesity | 232.00 | 7.31% | 72.04% | |
| Overweight | 816.00 | 25.73% | 97.76% | |
| Underweight | 71.00 | 2.24% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Newsletter_subscription | ||||
| False | 947.00 | 29.85% | 29.85% | |
| True | 2225.00 | 70.15% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Notifications_setting | ||||
| False | 65.00 | 2.05% | 2.05% | |
| True | 3107.00 | 97.95% | 100.0% | |
| Total | 3172.00 | 100.0% | - | |
| Training_days_setting | ||||
| True | 199.00 | 6.27% | 6.27% | |
| 2.0 | 222.00 | 7.0% | 13.27% | |
| 3.0 | 1326.00 | 41.8% | 55.08% | |
| 4.0 | 672.00 | 21.19% | 76.26% | |
| 5.0 | 566.00 | 17.84% | 94.1% | |
| 6.0 | 100.00 | 3.15% | 97.26% | |
| 7.0 | 87.00 | 2.74% | 100.0% | |
| Total | 3172.00 | 100.0% | - |
Among the selected users, 38% of them are female (1217 users) and 62% are male (1995 users). Users that decided that their activity level is very active is 10% (330 users),active 56% (1784 users) and sedentary 33% (1058 users). It is seen that the biggest group of users define themselves as active. Most of the users decided that their goal is gaining (weight, muscles) - it is 46% (1445) of all users, smaller group is for losing weight - 40% (1253) and the smallest group have antiaging goal - 15% (474). Over 94% of users set their app language to Spanish (2995 out of 3172 users) and only 6% decided on english (177 users). Most of users defined their body type as mid - 47% (1501 users), then thin - 44% (1390 users) and strong is the smallest group - 9% (281 users). The biggest group of users has BMI in normal range (65%, 2052 users), but 26% have overweight (817 users), 7% obesity (231 users) and the smallest group is underweight - 2% (72 users). Over 70% of users agreed on newsletter subscription (2225 users) and 30% didn't agree on them (947 users). Almost 98% of users turned on notification settings (3107 users) and 65 users (2%) turned them off. Most of the users decided on having training 3 times a week - 42% (1326 users), then 4 times a week - 21% (672 users), 5 times a week - 18% (566 users), 2 times a week - 7% (222 users), once a week - 6% (199 users), 6 times a week - 3% (100 users) and the smallest group is for 7 times a week - 3% (87 users).
| Total | 20.0 | 25.0 | 15.0 | 30.0 | 35.0 | 10.0 | 40.0 | 45.0 | 50.0 | 17.0 | 12.0 | 18.0 | 22.0 | 16.0 | 13.0 | 23.0 | 14.0 | 21.0 | 19.0 | 24.0 | 28.0 | 26.0 | 27.0 | 6.0 | 8.0 | 32.0 | 16.5 | 29.0 | 11.0 | 17.5 | 12.6 | 7.0 | 8.5 | 9.0 | 33.0 | 31.0 | 9.9 | 28.4 | 10.5 | 12.5 | 14.3 | 17.1 | 23.2 | 14.5 | 22.1 | 14.6 | 21.5 | 15.1 | 20.5 | 19.7 | 19.2 | 16.9 | 18.9 | 6.6 | 18.1 | 18.6 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 3172 | 837 | 629 | 507 | 466 | 242 | 162 | 111 | 47 | 26 | 13 | 13 | 11 | 10 | 10 | 9 | 8 | 6 | 6 | 5 | 4 | 4 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Percent | 100.0% | 26.39% | 19.83% | 15.98% | 14.69% | 7.63% | 5.11% | 3.5% | 1.48% | 0.82% | 0.41% | 0.41% | 0.35% | 0.32% | 0.32% | 0.28% | 0.25% | 0.19% | 0.19% | 0.16% | 0.13% | 0.13% | 0.09% | 0.09% | 0.09% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% |
By consideringbody_fat as a categorical variable, it can be seen that most of the users set their body fat level at 20% - 837 (26%) users, then at 25% of body fat - 629 (20%) users and at 15% of body fat - 507 (16%) users.
The variables taken into analysis will be:
Data taken are only the first rows of every session_execution based on their ID. Users executed 49428 sessions.
Variables:
will be taken into consideration as numerical variables. Later, difficulty_feedback_session_execution and enjoyment_feedback_session_execution will be taken as a categorical variables.
Below there are summary statistics for numeric variables.
| count | mean | std | min | 25% | 50% | 75% | max | var | skewness | kurtosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| difficulty_feedback_session_execution | 49428.00 | 5.70 | 1.55 | 1.00 | 5.00 | 5.00 | 7.00 | 10.00 | 2.41 | 0.36 | 0.77 |
| enjoyment_feedback_session_execution | 49428.00 | 3.62 | 0.81 | 1.00 | 3.00 | 3.00 | 4.00 | 5.00 | 0.65 | 0.31 | -0.42 |
| total_time_session_execution | 49428.00 | 1353.94 | 679.41 | 3.00 | 878.00 | 1337.00 | 1714.00 | 7839.00 | 461603.74 | 1.00 | 2.93 |
| total_reps_session_execution | 49428.00 | 257.26 | 161.98 | 1.00 | 150.00 | 242.00 | 316.00 | 2227.00 | 26238.61 | 1.52 | 5.46 |
| reps_per_min_session_execution | 49428.00 | 12.08 | 8.10 | 0.27 | 7.70 | 10.83 | 14.63 | 184.62 | 65.55 | 4.37 | 44.58 |
| calories_session_execution | 49428.00 | 83.03 | 50.78 | 0.08 | 49.21 | 75.56 | 105.02 | 548.57 | 2578.21 | 1.85 | 6.64 |
Difficulty feedback is on scale 1 to 10. Mean value of difficulty feedback for all executed sessions is 5.7 (SD 1.55), median is 5 (IQR 5 - 7). So difficulty is 'medium'. Enjoyment feedback is on scale 1 to 5. Average value of enjoyment is 3.6 (SD 0.8). Median is 3 (IQR 3 - 4), so the users, in average, enjoyed the workouts in 60%. Mean value of session execution total time is 1354 seconds (SD 679), so in average, time spend on executing session is 1354 seconds (about 23 minutes). Median value is 1337 seconds (IQR 878 - 1714). The maximum value of total time spent on session execution is 7839 seconds (about 131 minutes). In average, total number of reps in an executed session is 257 reps (SD 162). Median value is 242 reps in a session (IQR 150 - 316). Maximum number of reps executed in a session is 2227 reps. Average value of reps per minute in a session execution is 12 reps in a minute (SD 8), median value is 11 reps per minute (IQR 8 - 15). Maximum value is 185 reps in a minute. Mean value of calories burned in a session execution is 83 (SD 51), median value is 76 (IQR 49 - 105). Maximum value of burned calories in a session execution is 549 calories.
The distribution of data will be checked for every variable. Goodness of fit will depend on RSS.
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [1.11 sec] [RSS: 5.25924] [loc=5.000 scale=1.316] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=0.21801, loc=5, scale=1.31632)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.26 sec] [RSS: 51.7273] [loc=3.601 scale=0.804] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=1.96434, loc=3.60085, scale=0.803796)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.29 sec] [RSS: 8.68698e-08] [loc=1312.571 scale=542.506] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=1.1691, loc=1312.57, scale=542.506)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [1.05 sec] [RSS: 3.69759e-06] [loc=240.000 scale=113.319] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=0.973716, loc=240, scale=113.319)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[dweibull] [0.53 sec] [RSS: 0.000151602] [loc=10.777 scale=4.880] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ndweibull\nRSS(c=0.97646, loc=10.7773, scale=4.87958)'}, xlabel='Values', ylabel='Frequency'>)
[distfit] >fit.. [distfit] >transform.. [distfit] >[gamma] [0.39 sec] [RSS: 1.12187e-05] [loc=-3.225 scale=27.021] [distfit] >Compute confidence interval [parametric] [distfit] >plot..
(<Figure size 900x400 with 1 Axes>,
<AxesSubplot: title={'center': '\ngamma\nRSS(a=3.19118, loc=-3.22523, scale=27.021)'}, xlabel='Values', ylabel='Frequency'>)
The data don't follow normal distribution.
As a categorical variables:
will be taken into consideration. Difficulty feedback is on scale 1 to 10 and enjoyment feedback is on scale 1 to 5.
Below there are frequency tables and frequency plots for the variables.
| Frequency | Percent | Cumulative Percent | ||
|---|---|---|---|---|
| Variable | factors | |||
| Enjoyment feedback | ||||
| 1.0 | 271.00 | 0.55% | 0.55% | |
| 2.0 | 963.00 | 1.95% | 2.5% | |
| 3.0 | 24424.00 | 49.41% | 51.91% | |
| 4.0 | 15241.00 | 30.83% | 82.74% | |
| 5.0 | 8529.00 | 17.26% | 100.0% | |
| Total | 49428.00 | 100.0% | - | |
| Difficulty feedback | ||||
| 1.0 | 376.00 | 0.76% | 0.76% | |
| 2.0 | 614.00 | 1.24% | 2.0% | |
| 3.0 | 2035.00 | 4.12% | 6.12% | |
| 4.0 | 2787.00 | 5.64% | 11.76% | |
| 5.0 | 22455.00 | 45.43% | 57.19% | |
| 6.0 | 7604.00 | 15.38% | 72.57% | |
| 7.0 | 7164.00 | 14.49% | 87.07% | |
| 8.0 | 3703.00 | 7.49% | 94.56% | |
| 9.0 | 1759.00 | 3.56% | 98.12% | |
| 10.0 | 931.00 | 1.88% | 100.0% | |
| Total | 49428.00 | 100.0% | - |
When taking enjoyment feedback as a categorical variable, 49% (24424) of executed sessions have enjoyment feedback equal to 3. Almost 31% of session executions have enjoyment feedback equal to 4, 17% of executed sessions have enjoyment feedback equal to 5 (maximum one). Enjoyment feedback of session execution equal to 2 was given for 963 sessions (2% of all sessions executed). Only 0.5% (271) of all session executions had enjoyment feedback equal to 1.
When difficulty feedback is taken into consideration as a categorical variable, then over 45% of all session executions have difficulty given to 5, so it's medium. Only 0.8% (376) of difficulty of all session executions were graded at 1 and 1.9% (931) were graded at difficulty 10.
| Total | Session 2 | Session 1 | Session 3 | Session 4 | Session 5 | Session 6 | Session 7 | Session 8 | Session 9 | Session 10 | Sesion 1 | Session 11 | Session 12 | Session 13 | Session 14 | Session 16 | Session 17 | Session 18 | Session 15 | Session 19 | Regenerative | Mitochondrial activation | Test | Revitalizing | Session 21 | Session 22 | Session 20 | Session 24 | Sesion 23 | Session 27 | Session 26 | Metabolic sandwich 1 | Session 28 | Session 29 | Session 31 | Session 32 | Rewarding | Metabolic sandwich 2 | IRP | Session 33 | Session 34 | Session 36 | Session 25 | Session 38 | Session 37 | Metabolic sandwich 3 | Session 41 | Session 39 | Session 43 | Session 42 | Session 30 | Fundamentals - Session 1 | Session 44 | Metabolic sandwich 4 | Session 46 | Session 48 | Session 47 | Session 35 | Session 49 | Fundamentals - Session 2 | Fundamentals - Session 3 | Session 40 | Fundamentals - Session 5 | Session 50 | Fundamentals - Session 4 | Session 45 | Hypertrophy - Session 9 | Hypertrophy - Session 10 | Fundamentals - Session 7 | Fundamentals - Session 6 | Hypertrophy - Session 12 | Hypertrophy - Session 11 | Hypertrophy - Session 13 | Hypertrophy - Session 14 | Fundamentals - Session 8 | Strength - Session 17 | Hypertrophy - Session 15 | Hypertrophy - Session 16 | Strength - Session 19 | Strength - Session 18 | Strength - Session 20 | Strength - Session 21 | Strength - Session 23 | Strength - Session 22 | Muscular endurance - Session 25 | Strength - Session 24 | MuHu24.1 | Muscular endurance - Session 26 | Skill & Metabolic training - Session 29 | Muscular endurance - Session 28 | Muscular endurance - Session 27 | Skill & Metabolic training - Session 30 | Transitions & Strength - Session 33 | Skill & Metabolic training - Session 31 | Transitions & Global - Session 40 | Transitions & Global - Session 37 | Transitions & Strength - Session 35 | Transitions & Global - Session 39 | Transitions & Strength - Session 36 | MuHu30.1 | Transitions & Global - Session 38 | MuHu 1.2 | Transitions & Strength - Session 34 | Skill & Metabolic training - Session 32 | MuHu 3.2 | MuHu 5.2 | MuHu36.1 | MuHu 4.2 | MuHu42.1 | Session 23 | MuHu27.1 | MuHu25.1 | MuHu 7.2 | MuHu 9.2 | MuHu29.1 | MuHu 11.2 | MuHu 13.2 | MuHu 10.2 | MuHu35.1 | MuHu28.1 | MuHu31.1 | MuHu33.1 | MuHu 17.2 | MuHu 15.2 | Session MuHu 19.2 | MuHu37.1 | MuHu 16.2 | Session 52 | MuHu39.1 | MuHu43.1 | MuHu41.1 | MuHu34.1 | Session 54 | MuHu40.1 | MuHu 21.2 | Session 51 | Session 53 | Session 55 | MuHu45.1 | Session 56 | MuHu51.1 | MuHu 22.2 | MuHu49.1 | Session 59 | MuHu46.1 | Session 57 | Session 69 | Session 66 | Session 60 | Session 68 | Session 61 | Session 58 | MuHu53.1 | Session 62 | MuHu52.1 | Session 65 | Session 64 | Session 67 | MuHu31.2 | MuHu29.2 | MuHu1.3 | MuHu49.2 | MuHu41.2 | MuHu46.2 | MuHu55.1 | Session 63 | MuHu28.2 | TTO | MuHu40.2 | MuHu5.3 | MuHu43.2 | MuHu45.2 | MuHu4.3 | MuHu39.2 | MuHu27.2 | MuHu35.2 | MuHu34.2 | MuHu33.2 | MuHu3.3 | MuHu64.1 | MuHu59.2 | MuHu63.1 | MuHu53.2 | MuHu55.2 | MuHu57.1 | MuHu58.1 | MuHu25.2 | MuHu59.1 | MuHu52.2 | MuHu61.1 | MuHu65.1 | MuHu67.1 | MuHu65.2 | MuHu51.2 | MuHu37.2 | MuHu58.2 | MuHu61.2 | MuHu57.2 | MuHu69.1 | MuHu64.2 | CPH | MuHu71.1 | MuHu63.2 | MuHu70.1 | MuHu7.3 | MuHu9.3 | MuHu49.3 | MuHu69.2 | session 7 | MuHu10.3 | MuHu11.3 | MuHu15.3 | MuHu51.3 | MuHu53.3 | MuHu67.2 | Active Rest 3 | MuHu72.1 | MuHu70.2 | TTO & IRP | MuHu13.3 | MuHu55.3 | MuHu71.2 | MuHu27.3 | MuHu25.3 | SS & IT | MuHu72.2 | MuHu16.3 | MuHu17.3 | MuHu19.3 | MuHu21.3 | MuHu22.3 | SS & TTO | MuHu61.3 | MuHu52.3 | MuHu59.3 | MuHu57.3 | TBD | MuHu58.3 | MuHu65.3 | IR & TT | IRP & IR | Mobility | MuHu64.3 | TBD & IR | MuHu67.3 | MuHu70.3 | MuHu31.3 | MuHu29.3 | SS & TB | MuHu69.3 | MuHu63.3 | TTO & TB | CP | MuHu28.3 | MuHu71.3 | Interval At Time | ITP | IRP & TB | MuHu35.3 | MuHu33.3 | SS & IRP | MuHu34.3 | MuHu37.3 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 49428 | 3805 | 3552 | 3299 | 2986 | 2924 | 1649 | 1522 | 1406 | 1354 | 1239 | 1151 | 897 | 877 | 765 | 727 | 673 | 629 | 605 | 546 | 540 | 523 | 517 | 484 | 444 | 429 | 415 | 390 | 387 | 365 | 359 | 359 | 353 | 341 | 323 | 320 | 307 | 301 | 280 | 279 | 277 | 270 | 261 | 260 | 252 | 252 | 246 | 242 | 237 | 233 | 230 | 230 | 230 | 226 | 224 | 214 | 206 | 205 | 202 | 183 | 178 | 173 | 168 | 149 | 146 | 145 | 145 | 136 | 132 | 131 | 123 | 121 | 116 | 113 | 109 | 103 | 103 | 102 | 101 | 100 | 90 | 89 | 89 | 87 | 83 | 81 | 79 | 76 | 76 | 72 | 71 | 70 | 69 | 67 | 65 | 63 | 61 | 61 | 60 | 60 | 59 | 59 | 59 | 58 | 56 | 52 | 50 | 49 | 49 | 42 | 41 | 38 | 38 | 38 | 37 | 34 | 34 | 33 | 33 | 33 | 31 | 31 | 31 | 30 | 30 | 30 | 29 | 29 | 29 | 28 | 26 | 26 | 25 | 23 | 23 | 22 | 22 | 21 | 20 | 19 | 19 | 19 | 17 | 17 | 17 | 17 | 17 | 16 | 16 | 16 | 16 | 16 | 16 | 15 | 15 | 15 | 15 | 15 | 14 | 13 | 13 | 13 | 12 | 12 | 12 | 12 | 12 | 12 | 12 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 9 | 9 | 9 | 9 | 9 | 8 | 8 | 8 | 7 | 7 | 7 | 7 | 7 | 7 | 6 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Percent | 100.0% | 7.7% | 7.19% | 6.67% | 6.04% | 5.92% | 3.34% | 3.08% | 2.84% | 2.74% | 2.51% | 2.33% | 1.81% | 1.77% | 1.55% | 1.47% | 1.36% | 1.27% | 1.22% | 1.1% | 1.09% | 1.06% | 1.05% | 0.98% | 0.9% | 0.87% | 0.84% | 0.79% | 0.78% | 0.74% | 0.73% | 0.73% | 0.71% | 0.69% | 0.65% | 0.65% | 0.62% | 0.61% | 0.57% | 0.56% | 0.56% | 0.55% | 0.53% | 0.53% | 0.51% | 0.51% | 0.5% | 0.49% | 0.48% | 0.47% | 0.47% | 0.47% | 0.47% | 0.46% | 0.45% | 0.43% | 0.42% | 0.41% | 0.41% | 0.37% | 0.36% | 0.35% | 0.34% | 0.3% | 0.3% | 0.29% | 0.29% | 0.28% | 0.27% | 0.27% | 0.25% | 0.24% | 0.23% | 0.23% | 0.22% | 0.21% | 0.21% | 0.21% | 0.2% | 0.2% | 0.18% | 0.18% | 0.18% | 0.18% | 0.17% | 0.16% | 0.16% | 0.15% | 0.15% | 0.15% | 0.14% | 0.14% | 0.14% | 0.14% | 0.13% | 0.13% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.12% | 0.11% | 0.11% | 0.1% | 0.1% | 0.1% | 0.08% | 0.08% | 0.08% | 0.08% | 0.08% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.07% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.06% | 0.05% | 0.05% | 0.05% | 0.05% | 0.05% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.04% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.03% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.02% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.01% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
Most of the sessions executed didn't have the same name. The biggest number of session executions that had the same name is 3805 sessions (7.7%) and had the name Session 2. Some of the sessions, like MuHu 37.3 or SS & IRP were executed only once.
It is possible to plot number of sessions executed weekly by users. It is possible to check if user did achieve weekly goal of trainings. This approach may not be fully correct to identify how many days a week user did workout.
We can check that there is one user whose number of sessions executed is bigger than 300 and it is user 1718. Below there is a plot that shows how many sessions in a week (and in which week) have the user executed.
| id_users | YYYY/WW | days_a_week_session_exe | training_days_setting | training_days_goal_achieved | |
|---|---|---|---|---|---|
| 0 | 108.00 | 2021/23 | 1 | 2 | 0 |
| 1 | 108.00 | 2021/43 | 1 | 2 | 0 |
| 2 | 108.00 | 2021/49 | 2 | 2 | 1 |
| 3 | 108.00 | 2022/04 | 3 | 2 | 1 |
| 4 | 108.00 | 2022/14 | 1 | 2 | 0 |
| ... | ... | ... | ... | ... | ... |
| 20318 | 18127.00 | 2022/21 | 1 | 5 | 0 |
| 20319 | 18147.00 | 2022/21 | 1 | 7 | 0 |
| 20320 | 18157.00 | 2022/21 | 1 | 5 | 0 |
| 20321 | 18165.00 | 2022/21 | 3 | 5 | 0 |
| 20322 | 18174.00 | 2022/21 | 1 | 1 | 1 |
20323 rows × 5 columns
<AxesSubplot: xlabel='YYYY/WW'>
| YYYY/WW | 2021/43 | 2021/44 | 2021/45 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2021/50 | 2021/51 | 2021/52 | 2022/01 | 2022/02 | 2022/03 | 2022/04 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 | 2022/15 | 2022/16 | 2022/17 | 2022/18 | 2022/19 | 2022/20 | 2022/21 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id_session_execution | 8 | 15 | 12 | 11 | 11 | 11 | 12 | 11 | 12 | 14 | 9 | 12 | 13 | 9 | 8 | 7 | 9 | 8 | 8 | 9 | 7 | 8 | 9 | 10 | 11 | 10 | 11 | 10 | 10 | 10 | 6 |
Below, there is also data about this user - this is very active male, that has a goal to gain muscles, and his body type is strong. He has 83 kg and is 184 cm tall. Body fat is on 15%. He agreed on newsletter and notifications, set the name of the app to Spanish and training days are 5 a week. This user did 311 sessions and spent 452170 seconds on them (7536 minutes, almost 126 hours).
| id_users | created_at_users | updated_at_users | gender | date_of_birth | height | weight | activity_level | goal | body_type | body_fat | newsletter_subscription | notifications_setting | training_days_setting | language | points | scientific_data_usage | best_weekly_streak_users | BMI | BMI_category | total_sessions_users2 | total_time_users2 | total_reps_users2 | reps_per_session_users2 | total_calories_users2 | kcal_per_session_users2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 89868 | 1718.00 | 2021-10-25 11:02:12.043287 | 2022-09-11 05:44:44.460912 | male | 1981-03-07 | 184.00 | 83.00 | very active | gain | strong | 15.00 | True | True | 5.00 | es | 1810142.00 | False | 44.00 | 24.52 | Normal | 311.00 | 452170.00 | 120390.00 | 387.11 | 31452.30 | 101.13 |
Below there is a plot and a table with number of days a week the user 1718 had done a workout and a red line that represent training days setting.
<matplotlib.legend.Legend at 0x7f34c45d34c0>
| YYYY/WW | 2021/43 | 2021/44 | 2021/45 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2021/50 | 2021/51 | 2021/52 | 2022/01 | 2022/02 | 2022/03 | 2022/04 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 | 2022/15 | 2022/16 | 2022/17 | 2022/18 | 2022/19 | 2022/20 | 2022/21 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| days_a_week_session_exe | 3 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 6 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 4 |
| training_days_setting | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
Now, for example user 4494. Below there is a plot of number of session executed in each week.
<AxesSubplot: xlabel='YYYY/WW'>
| YYYY/WW | 2021/43 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2022/02 | 2022/03 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id_session_execution | 1 | 3 | 2 | 2 | 1 | 4 | 3 | 3 | 3 | 4 | 3 | 3 | 4 | 5 | 3 | 3 | 3 |
This user is active male with goal to gain muscles and thin body_type. Body fat is on 20% level. He has 62 kg and is 168 cm tall. His BMI is on normal level. His app was set on Spanish language. He set his training days at 3 days a week. He executed 50 sessions and total time of all sessions is 74831 seconds (over 1247 minutes, almost 21 hours).
| id_users | created_at_users | updated_at_users | gender | date_of_birth | height | weight | activity_level | goal | body_type | body_fat | newsletter_subscription | notifications_setting | training_days_setting | language | points | scientific_data_usage | best_weekly_streak_users | BMI | BMI_category | total_sessions_users2 | total_time_users2 | total_reps_users2 | reps_per_session_users2 | total_calories_users2 | kcal_per_session_users2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 104007 | 4494.00 | 2021-10-28 06:06:18.825845 | 2022-04-07 09:43:19.433396 | male | 1978-11-11 | 168.00 | 62.00 | active | gain | thin | 20.00 | True | True | 3.00 | es | 91440.00 | False | 9.00 | 21.97 | Normal | 50.00 | 74831.00 | 9610.00 | 192.20 | 3218.41 | 64.37 |
Below there is a plot with number of days when the workout was done and training days setting value.
<matplotlib.legend.Legend at 0x7f34c504b610>
| YYYY/WW | 2021/43 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2022/02 | 2022/03 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| days_a_week_session_exe | 1 | 3 | 2 | 2 | 1 | 4 | 3 | 3 | 3 | 4 | 3 | 3 | 4 | 4 | 3 | 3 | 3 |
| training_days_setting | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
The other user is a user that is said to have best weekly streak equal to 49. It is not true, but we will see that user. It is user 1285. Below there is a plot and table with number of sessions executed in each week.
<AxesSubplot: xlabel='YYYY/WW'>
| YYYY/WW | 2021/44 | 2021/45 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2021/50 | 2021/51 | 2021/52 | 2022/01 | 2022/02 | 2022/03 | 2022/04 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 | 2022/15 | 2022/16 | 2022/17 | 2022/18 | 2022/19 | 2022/20 | 2022/21 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id_session_execution | 5 | 5 | 5 | 6 | 5 | 6 | 4 | 11 | 4 | 7 | 5 | 6 | 4 | 3 | 6 | 3 | 3 | 6 | 3 | 9 | 4 | 2 | 2 | 5 | 1 | 2 | 2 | 4 | 3 | 1 |
The user is active male with goal of losing weight and mid body type. He is 177 cm tall and his weight is equal to 84 kg. According to BMI number, he is overweight. His body fat has 30% and his app language is Spanish. He did 132 session in total and spent 147315 seconds (2455 minutes, almost 41 hours) doing them.
| id_users | created_at_users | updated_at_users | gender | date_of_birth | height | weight | activity_level | goal | body_type | body_fat | newsletter_subscription | notifications_setting | training_days_setting | language | points | scientific_data_usage | best_weekly_streak_users | BMI | BMI_category | total_sessions_users2 | total_time_users2 | total_reps_users2 | reps_per_session_users2 | total_calories_users2 | kcal_per_session_users2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 116793 | 1285.00 | 2021-10-25 11:00:13.463122 | 2022-09-09 16:41:32.933491 | male | 1979-12-08 | 177.00 | 84.00 | active | lose | mid | 30.00 | True | True | 5.00 | es | 1006620.00 | True | 49.00 | 26.81 | Overweight | 132.00 | 147314.50 | 34942.00 | 264.71 | 11109.87 | 84.17 |
Below there is a plot with number of days when the workout was done and training days setting value.
<matplotlib.legend.Legend at 0x7f34bb3c1f00>
| YYYY/WW | 2021/44 | 2021/45 | 2021/46 | 2021/47 | 2021/48 | 2021/49 | 2021/50 | 2021/51 | 2021/52 | 2022/01 | 2022/02 | 2022/03 | 2022/04 | 2022/05 | 2022/06 | 2022/07 | 2022/08 | 2022/09 | 2022/10 | 2022/11 | 2022/12 | 2022/13 | 2022/14 | 2022/15 | 2022/16 | 2022/17 | 2022/18 | 2022/19 | 2022/20 | 2022/21 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| days_a_week_session_exe | 2 | 4 | 4 | 4 | 4 | 4 | 4 | 7 | 4 | 5 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 3 | 6 | 3 | 2 | 2 | 3 | 1 | 2 | 2 | 4 | 3 | 1 |
| training_days_setting | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
The user achieved only 3 weeks when comparing number of days a week the user did a workout and training days setting, so best_weekly_streak variable doesn't give correct numbers.